As I reported here, a new iPhone app is being used in Milton Keynes to capture and share conversations in the community. I was given an impromptu demonstration on the spot by Corrina Milner and Andy MacDermott – but it was difficult the see the detail. I asked if we could see some screen shots – and these were kind provided by David Livermore, assistance chief executive at Communityaction:MK. Below David explains why they developed the app. As I explained in the earlier post, it isn’t yet in the official app store.
Community Action:MK manage a team of area based community workers called, Community Mobilisers. Over the last couple of years we have been working to refine our engagement and analysis processes, we knew that the levels of discussion taking place within communities were rich, deep and varied yet, in terms of having any real impact in changing service delivery within communities, it was patchy and ad-hoc with a complete over reliance upon survey data from authorities in order to understand what people are thinking. This, survey-based approach is based on the assumption that you know the right questions to ask and that people within communities don’t discuss anything until they’re asked!
We felt that there was a better way of understanding what conversations were going on on the ground at any one time, enable us to spot trends as they emerge and respond to them more cohesively and swiftly. The app is a tool for the Community Mobilisers to record the thread of the conversation they have with individuals, be it an idea, an interest or an issue. Over a period of a month a Mobiliser will typically have between 80-100 meaningful conversations (ie those which go a bit further that the ‘Hi’ in the street – which we also positively encourage!)
These conversations are then entered into the app, either as text, audio or video clips (pictures can also be used). They are then sent into the ‘Cloud’ where they are categorised, themed and analysed and then displayed within an overview screen as pie charts and statistics. We can apply specific filters to narrow down the data field and there is also an internal search engine which can identify any conversations which have included a specific word!